Brief Introduction:
I got a degree in Computer Science (Honors) from Chuvash State University, Cheboksary, Russia, in 1999. While studying there, I was working on a numerical analysis project under the supervision of an amazingly talented engineer and wonderful man, Dr. Sergey Kouzmin (1953-2009) from Dynamics LTD . My final-year diploma project was based on the work I was doing in Moscow at the Center of Macroeconomic Research and Forecasts of Plekhanov Economic Academy in 1998-1999.

In 1999 I was one of three students from Russia to be awarded the Shell Centenary Scholarship to study for the Master of Science (MSc) program in the UK. I got an MSc in non-symbolic artificial intelligence and learning from data from the University of Edinburgh in 2000 (distinction, the best dissertation award). In 2001 I was working on engineering applications of machine learning at the Chair of Manufacturing Technology of the University of Erlangen-Nuernberg.

In 2002-2005 I was a PhD student in the Institute for Adaptive and Neural Computation, working on theoretical and practical aspects of probabilistic machine learning in large-scale stochastic systems. On completion of my PhD in 2005, I continued as a post-doctoral researcher applying machine learning to compiler optimization. I contributed to the development of the methods used in the acclaimed Milepost GCC compiler (which received substantial public coverage in the specialized and general media, including the Wall Street Journal and CNN Money). I then co-founded a scientific startup company Level E Limited applying machine learning and data analysis to financial risk management and high-frequency trading. My responsibilities of a CSO and executive director included heading and coordinating the work of a multidisciplinary group of 6 researchers (with doctoral degrees in engineering, quantitative finance, and computer science), strategic planning, fund-raising, and investor relations. After selling my stake in the company in 2009, I became a full-time member of the UoE's Centre for Population Health Sciences and a visiting member of the School of Informatics.

My current work focuses on machine learning methods and applications to medical, biological, and financial tasks, including sparse Bayesian extensions of instrumental variable methods for identifying causes of complex diseases, learning structures of large-scale latent variable models (with applications to biological pathways and financial risk management), and predictive methods for personalized health risk predictions.

I am playing the key role in the formation and fundraising for a new startup Pharmatics, which will develop intelligent solutions for personalized medicine and drug development.

Some of my other interests are reading and wild forest hiking. I am an active follower of the current Russian political and business news.

Page last updated: Jul. 28, 2011

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